Big data noise has reached the point where most are reaching for the ear plugs. And with any good hype bubble, the naysayers are now grabbing attention with contrarian positions. For example, The New York Times expressed doubt about the economic viability of big data in "Is Big Data an Economic Big Dud?" This post grabbed a lot of attention, but, like many others I read, it fundamentally misses the point of what big data is all about and why it's important. The article compares the productivity boom associated with the first wave of the Internet to the lack of growth experienced since the inception of "big data"; it implies that big data’s expected economic impact may not happen. Furthermore, the article implies that big data is something that firms will do or implement. Thinking about big data this way or differentiating between data sets as big, medium, or small is dangerous. It leads to chasing rabbits down holes.

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I get a lot of questions about the best way for developers to move to the cloud. That’s a good thing, because trying to forklift your existing applications as is isn’t a recipe for success. Building elastic applications requires a focus on statelessness, atomicity, idempotence, and parallelism — qualities that are not often built into traditional “scale-up” applications. But I also get questions that I think are a bit beside the point, like “Which is better: infrastructure-as-a-service (IaaS) or platform-as-a-service (PaaS)?” My answer: "It depends on what you’re trying to accomplish, your teams’ skills, and how you like to consume software from ISVs.” That first question is often followed up by a second: “Who’s the leader in the public cloud space?” It’s like asking, “Who's the leading car maker?” There’s a volume answer and there’s a performance answer. It’s one answer if you like pickups, and it’s a different answer if you want an EV. You have to look at your individual needs and match the capabilities of the car and its “ilities” to those needs. That’s how I think we’re starting to see developer adoption of cloud services evolve, based around the capabilities of individual services — not the *aaS taxonomy that we pundits and vendors apply to what’s out there. This approach to service-based adoption is reflected in data from our Forrsights Developer Survey, Q1 2013, so I've chosen publish some of it today to illustrate the adoption differences we see from service to service.